Welcome to the ‘Get started’ page of the jfa package. jfa is an R package that provides Bayesian and classical statistical methods for audit sampling, data auditing, and algorithm auditing. This page points you to the vignettes accompanying each of these three subjects.
Firstly, jfa facilitates statistical audit sampling. That is, the package provides functions for planning, performing, and evaluating an audit sample compliant with international standards on auditing (American Institute of Certified Public Accountants (AICPA), 2021; International Auditing and Assurance Standards Board (IAASB), 2018; Public Company Accounting Oversight Board (PCAOB), 2020).
Secondly, jfa facilitates statistical data auditing. That is, the package includes functions for auditing data, such as testing the distribution of first digits of a data set against Benford’s law, or assessing whether a data set includes an unusual amount of repeated values.
Finally, jfa facilitates statistical algorithm auditing. That is, the package implements functions for auditing algorithms, such as computing fairness metrics and testing the equality of parity metrics across protected groups.